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Cited by 230

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Human resource management – a survey of practices within family and non‐family firms

Reid, Renee S., Adams, John S.·2001·Journal of European Industrial Training

Abstract

Much of the literature relating to human resource management (HRM) has attempted to demonstrate that the “Human resource” is the most valued asset in a company. Large companies have revolutionised their approach to the training and development of their personnel in order to maximise their “competitive edge”. Hotly debated is whether investment in “good HRM” is linked to commercial success. However, very little is known about HRM practices within the small‐ to medium‐size business (SME) and even less is known about the practice within a family business. This survey describes the HRM practices of SMEs (both family and non‐family businesses) in Northern Ireland. Comparisons between the groups are made and findings suggest that family businesses practice HRM differently than their non‐family counterparts. Implications for the training and development of these two groups question whether family businesses need to be treated as a “special case”.

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Crossref · 10.1108/03090590110401782

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Metadata

Authors
Reid, R. S., & Adams, J. S.
Venue
Journal of European Industrial Training
Publisher
Emerald
Published
2001-08-01
Volume
25
Issue
6
Pages
310-320
ISSN
0309-0590 (ISSN-L)
OpenAlex
W2018531136
Cited by
230
References
1
FWCI
4.48
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Human resource management – a survey of practices within family and non‐family firms. https://app.cochat.ai/papers/10.1108/03090590110401782
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Reid, R. S., & Adams, J. S. (2001). Human resource management – a survey of practices within family and non‐family firms. Journal of European Industrial Training. https://doi.org/10.1108/03090590110401782

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.